Combining Laser Range Finder to Implement SLAM for Vehicle Navigation

Abstract

This thesis describes the implementation of multi-sensor integrated positioning algorithms for vehicular navigation and simultaneous localization and mapping (SLAM) The positioning algorithm provides precision position information in an outdoor environment The positioning accuracy for vehicle navigation is very important Nowadays Global Positioning System (GPS) has been developed maturely and widely used in vehicle navigation However the positioning accuracy of GPS signals of moving vehicle is easily affected by the influence of environment such as shelter and multipath from the building in the city The signal would be interrupted In many studies the integration navigation technology of Inertial Navigation System (INS) and GPS is used to estimate position velocity and attitude of vehicle based on Extended Kalman Filter (EKF) However it is possible for GPS signals to lost for a long time causing cumulative error in the estimation In order to solve this problem this study adds the laser range finder to integrate the GPS and IMU The laser range finder scans surrounding object as a reference point (landmark) when the vehicle is driving and then the relative distance and angle between the vehicle and the landmarks are acquired The measured information can correct vehicle state which increase the precision and the reliability of the navigation This integration navigation technology is developed in SLAM based on EKF This research utilizes the Light-weight Electric Vehicle (LEV) equipped GPS / IMU / Laser range finger The sensors are integrated into the embedded platform for real-time receiving when the electric vehicle is driving in campus The received measurement data are analyzed and processed and then SLAM algorithm based on EKF (EKF-SLAM) is used to estimate vehicle state which is verified and post processing on the computer

Date of Award	2014 Aug 5
Original language	English
Supervisor	Jyh-Chin Juang (Supervisor)